docs/ipynb/export.ipynb
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"!pip install autokeras"
]
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"import numpy as np\n",
"from keras.datasets import mnist\n",
"from keras.models import load_model\n",
"\n",
"import autokeras as ak"
]
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"You can easily export your model the best model found by AutoKeras as a Keras\n",
"Model.\n",
"\n",
"The following example uses [ImageClassifier](/image_classifier) as an example.\n",
"All the tasks and the [AutoModel](/auto_model/#automodel-class) has this\n",
"[export_model](/auto_model/#export_model-method) function.\n"
]
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"(x_train, y_train), (x_test, y_test) = mnist.load_data()\n",
"\n",
"# Initialize the image classifier.\n",
"clf = ak.ImageClassifier(\n",
" overwrite=True, max_trials=1\n",
") # Try only 1 model.(Increase accordingly)\n",
"# Feed the image classifier with training data.\n",
"clf.fit(x_train, y_train, epochs=1) # Change no of epochs to improve the model\n",
"# Export as a Keras Model.\n",
"model = clf.export_model()\n",
"\n",
"print(type(model)) # <class 'tensorflow.python.keras.engine.training.Model'>\n",
"\n",
"model.save(\"model_autokeras.keras\")\n",
"\n",
"\n",
"loaded_model = load_model(\n",
" \"model_autokeras.keras\", custom_objects=ak.CUSTOM_OBJECTS\n",
")\n",
"\n",
"predicted_y = loaded_model.predict(np.expand_dims(x_test, -1))\n",
"print(predicted_y)"
]
}
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